Build an insights-driven org

Big Data Survey

Boris Evelson
Vice President, Principal Analyst
May 18, 2011

Forrester is in the middle of a major research effort on various Big Data-related topics. As part of this research, we’ll be kicking off a client survey shortly. I’d like to solicit everyone’s input on the survey questions and answer options. Here’s the first draft. What am I missing?

  1. Scope. What is the scope of your Big Data initiative?
    1. Enterprise
    2. LOB
    3. Departmental
    4. Regional
    5. Project-based
  2. Status. What is the status of your Big Data initiative?
    1. In production
    2. Piloting
    3. Testing
    4. Evaluating
  3. Industry. Are the questions you are trying to address with your Big Data initiative general or industry-specific?
    1. General
    2. Industry-specific
    3. Both
  4. Domains. What enterprise areas does your Big Data initiative address?
    1. Sales
    2. Marketing
    3. Customer service
    4. Finance
    5. HR
    6. Product development
    7. Operations
    8. Logistics
    9. Brand management
    10. IT analytics
    11. Risk management
  5. Why BigData? What are the main business requirements or inadequacies of earlier-generation BI/DW/ET technologies, applications, and architecture that are causing you to consider or implement Big Data?
    1. Data volume
      1. <10Tb
      2. 10-100Tb
      3. 100Tb-1Pb
      4. >1Pb
    2. Velocity of change and scope/requirements unpredictability
    3. Data diversity
    4. Analysis-driven requirements (Big Data) vs. requirements-driven analysis (traditional BI/DW)
    5. Cost. Big Data solutions are less expensive than traditional ETL/DW/BI solutions
  6. BigData as input to BI apps. Do you plan to use Big Data exploraton results for
    1. Inputs into BI applications
    2. Specifications for BI applications
  7. Types of data. What types of data/records are you planning to analyze using BigData technologies?
    1. Transacational data from enterprise applications

    2. Clickstream

    3. Unstructured content from email, office documents, etc

    4. Social media (Facebook, Twitter, etc) data

    5. Sensor / Machine/Device Data

    6. Locational/Geospatial Data

    7. Scientific/Genomic data

    8. Image (large Video/Photographic) Data

  8. Ownership. Who owns or drives your BigData initiative?
    1. Mostly business-driven, with minimal IT support
    2. Business/IT collaboration
    3. Mostly IT driven, with minimal business involvement
  9. External assistance. Are you doing this on your own or with help of consultants and other external SMEs?
    1. All internal
    2. Mostly internal, with some help from third parties
    3. Mostly third parties under our direction and supervision
    4. All outsourced
  10. Integration with BI, DW, etc. How is your Big Data initiative integrated with, embedded in, or part of your other BI/DW/ETL/data governance/MDM initiatives, if at all?
    1. Big Data and BI/DW/ETL are just different areas of a broad information management activity
    2. Big Data and BI/DW/ETL are separate initiatives with close coordination
    3. Big Data and BI/DW/ETL are separate initiatives with some coordination
    4. Big Data and BI/DW/ETL are separate initiatives
  11. Integration with advanced analytics. How is your Big Data initiative integrated with, embedded in, or part of your other advanced analytics (statistical analysis, data mining, predictive modeling, etc.) initiatives, if at all?
    1. Big Data and advanced analytics are just different areas of a broad information management activity
    2. Big Data and advanced analytics are separate initiatives with close coordination
    3. Big Data and advanced analytics are separate initiatives with some coordination
    4. Big Data and advanced analytics are separate initiatives
  12. Project management. Do you run your Big Data initiative using the same or different PMO standards than BI/DW/ETL?
    1. Same
    2. Different
  13. Software development. Do you run your Big Data initiative using the same or different SDLC standards than BI/DW/ETL?
    1. Same
    2. Different
  14. Integration with enterprise apps. Do your Big Data applications stand on their own or are they tightly integrated or embedded with any of the following?
    1. Enterprise applications (ERP, CRM)
    2. Business processes (BPM)
    3. Business rules (BRE)
  15. Concerns. Are the following concerns higher, lower, or the same when dealing with Big Data initiatives as compared with earlier-generation BI/DW/ETL applications?
    1. Security
    2. Privacy
    3. Operational risk (liability, reputation, etc.)
  16. Retention. Do you intend to retain you raw Big Data post the exploration /analysis stage?
    1. No
    2. Yes, for compliance
    3. Yes, for re-processing, more analysis
  17. Big Data technology. What technology do you use for BigData applications?
    1. Data integration tools based on BigData technology
    2. DW tools based on BigData technology
    3. BI tools based on BigData technology
    4. Advanced Analytics tools based on BigData technology
  18. App delivery model. Do you run your Big Data applications on premises or in the cloud?
    1. On-premises
    2. Hosted/private cloud
    3. Public cloud
  19. Commercial vs. Open Source. Do you use mostly
    1. Open source Big Data technology (Hadoop, MapReduce, Cassandra, and the other Apache open source specs)
    2. Commercial source Big Data tools
  20. Business case. Do you have a business case for the Big Data initaitive in place?
    1. Yes, with a proven ROI
    2. Yes, with a projected ROI
    3. Yes, with intangible benefits only
    4. No business case
  21. Metrics. How do you plan to measure the success of the Big Data inititative?
    1. With quantitative metrics tied to business performance
    2. With qualitative metrics tied to business performance
    3. With quantitative metrics tied to IT performance
    4. With qualitative metrics tied to IT performance
    5. No specific measurement methodology in place
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